Strategies for Effective Application of Robotic Process Automation

RPA extends automation into use cases that require human interaction with applications. It simplifies creation of automated workflows, but doesn’t democratize an inherently technical system. Technical professionals must understand RPA’s capabilities and limitations. 

KEY INSIGHTFULL DOCUMENT 

Overview 

Key Findings 

• RPA is a discrete set of automation tools and technologies that extends and complements existing automation disciplines. 
• RPA recorders are useful in rudimentary scenarios, but more robust automation will almost always require manipulating the automation workflow modules directly. Expectations may need to be reset. 

• Success with RPA depends more on choosing the right processes to automate, rather than the right technology. 
• A robot validation framework, often managed by a COE, should be a critical part of any enterprise RPA rollout. 
• While the low- or no-code environment creates opportunities for nontechnical persons to contribute to RPA systems, the entirety of operations, validation, troubleshooting and maintenance will almost certainly require technical professional skill sets. 

Recommendations 

Technical professionals adopting automation as a component of their efforts to modernize their data and analytics programs should: 

• Establish operational ownership and maintenance of the RPA program and platform within IT, even if script authoring is done by other organizations. 
• Own the validation, publication and management of RPA robots and their access to data. 
• Communicate a roadmap of evolving criteria for well-suited and poorly suited processes, and data that will or won’t be automated with RPA. 
• Focus on the robot validation framework to ensure robust automation, regardless of who creates the automation scripts or how they are created.